An agent can perform erroneous actions. Despite such errors, one might want to understand what the agent tried to achieve. Such understanding is important, for example, in intelligent tutoring and expert critiquing systems. In intelligent tutoring, feedback to the agent--i.e, the student--should focus on which actions made sense and which did not. To achieve such understanding, we propose a combined planning and plan recognition approach. This paper focuses on plan-based plan recognition. We describe a generic recognition algorithm and show how it can be used for plan recognition and critiquing. The approach is illustrated using a real-world application in the area of multi-media tutoring of ship crisis management.

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